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arxiv: 1304.1030 · v1 · pith:U34XNKYCnew · submitted 2013-04-03 · 🧮 math.ST · stat.TH

A note on a Bayesian nonparametric estimator of the discovery probability

classification 🧮 math.ST stat.TH
keywords bayesianestimatorexplicitnonparametricpoisson-dirichletpriorsprobabilityresult
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Favaro, Lijoi, and Pruenster (2012, Biometrics, 68, 1188--1196) derive a novel Bayesian nonparametric estimator of the probability of detecting at the $(n+m+1)$th observation a species already observed with any given frequency in an enlarged sample of size $n+m$, conditionally on a basic sample of size $n$. Unfortunately the general result under Gibbs priors (Theorem 2), and consequently the explicit result under $(\alpha, \theta)$ Poisson-Dirichlet priors (Proposition 3), appear to be wrong. Here we provide the correct formulas for both the results, obtained by means of a new technique devised in Cerquetti (2013). We verify the correctness of our derivation by an explicit counterproof for the two-parameter Poisson-Dirichlet case.

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